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Robust Nonparametric Inference

机译:强大的非参数推断

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摘要

In this article; we provide a personal review of the literature on nonpara-metric and robust tools in the standard univariate and multivariate location and scatter, as well as linear regression problems, with a special focus on sign and rank methods,their equivariance and invariance properties, and their robustness and efficiency. Beyond parametric models, the population quantities of interest are often formulated as location, scatter, skewness, kurtosis and other functionals. Some old and recent tools for model checking, dimension reduction, and subspace estimation in wide semiparametric models are discussed. We also discuss recent extensions of procedures in certain nonstandard semiparametric cases including clustered and matrix-valued data. Ourpersonal list of important unsolved and future issues is provided.
机译:在本文中; 我们在标准单变量和多变量和多变量位置和散射以及线性回归问题中提供对非Para-undric和强大的工具的文献的个人审查,以及线性回归问题,特别关注标志和等级方法,它们的标准和不变性属性及其 鲁棒性和效率。 除了参数模型之外,人口的兴趣数量通常常用为位置,散射,偏光,峰和其他功能。 讨论了一些旧的和最近的模型检查,尺寸减小和宽半摩擦模型中的子空间估计工具。 我们还讨论了最近的某些非标准半导体案例中的程序扩展,包括集群和矩阵值数据。 提供了重要的未解决和未来问题的武器名单。

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